Microalgae Commercialization Using Renewable Lignocellulose Is Economically and Environmentally Viable.

Conventional phototrophic cultivation for microalgae production suffers from low and unstable biomass productivity due to limited and unreliable light transmission outdoors. Alternatively, the use of a renewable lignocellulose-derived carbon source, cellulosic hydrolysate, offers a cost-effective and sustainable pathway to cultivate microalgae heterotrophically with high algal growth rate and terminal density. In this study, we evaluate the feasibility of cellulosic hydrolysate-mediated heterotrophic cultivation (Cel-HC) for microalgae production by performing economic and environmental comparisons with phototrophic cultivation through techno-economic analysis and life cycle assessment. We estimate a minimum selling price (MSP) of 4722 USD/t for producing high-purity microalgae through Cel-HC considering annual biomass productivity of 300 t (dry weight), which is competitive with the conventional phototrophic raceway pond system. Revenues from the lignocellulose-derived co-products, xylose and fulvic acid fertilizer, could further reduce the MSP to 2976 USD/t, highlighting the advantages of simultaneously producing high-value products and biofuels in an integrated biorefinery scheme. Further, Cel-HC exhibits lower environmental impacts, such as cumulative energy demand and greenhouse gas emissions, than phototrophic systems, revealing its potential to reduce the carbon intensity of algae-derived commodities. Our results demonstrate the economic and environmental competitiveness of heterotrophic microalgae production based on renewable bio-feedstock of lignocellulose.

Improving litterfall production prediction in China under variable environmental conditions using machine learning algorithms.

Litterfall production is a major process within forest ecosystems that plays a crucial role in the global carbon cycle. Accordingly, studies have explored the abiotic and biotic features that influence litterfall production. In addition to traditional statistical models, the rapid development of nonparametric and nonlinear machine learning models, such as random forest (RF), light gradient boosting machine (LightGBM), and categorical boosting (CatBoost), have provided new methods of predicting the production of forest litterfall. Here, we evaluated the ability of the abovementioned models and mixed effect random forest (MERF) models to predict total annual litterfall production-based on several abiotic and biotic features-using 968 records from 314 forest sites covering the full geographical range of Chinese forests. In general, machine learning models were found to outperform linear mixed models. In particular, the MERF models ranked the highest in terms of performance (R2 = 0.7), which may be attributed to their ability to characterize nonlinear relationships between features and litterfall production. The key drivers were climate-related features and forest age, with the mean annual temperature and age positively correlated with litterfall production. Furthermore, the correlation between forest type and litterfall production was more significant for needleleaf forests than for other forest types. For needleleaf and broadleaf forests in several regions in China, the future litterfall production was predicted to be the highest under IPCC representative concentration pathway (RCP) 8.5, followed by RCP 4.5, RCP 2.6, and the original scenarios (sample data). Improved models to better understand and estimate litterfall production in forests at present and in the future are required for forest management planning to minimize the negative impacts of climate change on forest ecosystems.

Electrocatalysis for Chemical and Fuel Production: Investigating Climate Change Mitigation Potential and Economic Feasibility.

The manufacture of goods from oil, coal, or gas to everyday consumer products comprises in more or less all cases at least one catalytic step. Compared to conventional hydrothermal catalysis, electrocatalysis possesses the advantage of mild operational conditions and high selectivity, yet the potential energy savings and climate change mitigation have rarely been assessed. This study conducted a life cycle assessment (LCA) for the electrocatalytic oxidation of crude glycerol to produce lactic acid, one of the most common platform chemicals. The LCA results demonstrated a 31% reduction in global warming potential (GWP) compared to the benchmark (bio- and chemocatalytic) processes. Additionally, electrocatalysis yielded a synergetic potential to mitigate climate change depending on the scenario. For example, electrocatalysis combined with a low-carbon-intensity grid can reduce GWP by 57% if the process yields lactic acid and lignocellulosic biofuel as compared to a conventional fossil-based system with functionally equivalent products. This illustrates the potential of electrocatalysis as an important contributor to climate change mitigation across multiple industries. A technoeconomic analysis (TEA) for electrocatalytic lactic acid production indicated considerable challenges in economic feasibility due to the significant upfront capital cost. This challenge could be largely addressed by enabling dual redox processing to produce separate streams of renewable chemicals and biofuels simultaneously.

Meta-analysis and Harmonization of Life Cycle Assessment Studies for Algae Biofuels.

Algae biodiesel (BioD) and renewable diesel (RD) have been recognized as potential solutions to mitigating fossil-fuel consumption and the associated environmental issues. Life cycle assessment (LCA) has been used by many researchers to evaluate the potential environmental impacts of these algae-derived fuels, yielding a wide range of results and, in some cases, even differing on indicating whether these fuels are preferred to petroleum-derived fuels or not. This meta-analysis reviews the methodological preferences and results for energy consumption, greenhouse gas emissions, and water consumption for 54 LCA studies that considered algae BioD and RD. The significant variation in reported results can be primarily attributed to the difference in scope, assumptions, and data sources. To minimize the variation in life cycle inventory calculations, a harmonized inventory data set including both nominal and uncertainty data is calculated for each stage of the algae-derived fuel life cycle.

Review of Water Consumption and Water Conservation Technologies in the Algal Biofuel Process.

Although water is one of the most critical factors affecting the sustainable development of algal biofuels, it is much less studied as compared to the extensive research on algal biofuel production technologies. This paper provides a review of the recent studies on water consumption of the algae biofuel process and presents the water conservation technologies applicable at different stages of the algal biofuel process. Open ponds tend to have much higher water consumption (216 to 2000 gal/gal) than photobioreactors (25 to 72 gal/gal). Algae growth accounts for the highest water consumption (165 to 2000 gal/gal) in the open pond system. Water consumption during harvesting, oil extraction, and biofuel conversion are much less compared with the growth stage. Potential water conservation opportunities include technology innovations and better management practices at different stages of algal biofuel production.

Chitin Nanofibers Enable the Colloidal Dispersion of Carbon Nanomaterials in Aqueous Phase and Hybrid Material Coassembly.

Chitin nanofibrils (ChNF) sourced from discarded marine biomass are shown as effective stabilizers of carbon nanomaterials in aqueous media. Such stabilization is evaluated for carbon nanotubes (CNT) considering spatial and temporal perspectives by using experimental (small-angle X-ray scattering, among others) and theoretical (atomistic simulation) approaches. We reveal that the coassembly of ChNF and CNT is governed by hydrophobic interactions, while electrostatic repulsion drives the colloidal stabilization of the hybrid ChNF/CNT system. Related effects are found to be transferable to multiwalled carbon nanotubes and graphene nanosheets. The observations explain the functionality of hybrid membranes obtained by aqueous phase processing, which benefit from an excellent areal mass distribution (correlated to piezoresistivity), also contributing to high electromechanical performance. The water resistance and flexibility of the ChNF/CNT membranes (along with its tensile strength at break of 190 MPa, conductivity of up to 426 S/cm, and piezoresistivity and light absorption properties) are conveniently combined in a device demonstration, a sunlight water evaporator. The latter is shown to present a high evaporation rate (as high as 1.425 kg water m-2 h-1 under one sun illumination) and recyclability.

Life cycle assessment of bamboo products: Review and harmonization.

Bamboo is considered a promising solution to mitigate climate change because of its carbon sequestration capability and versatile applications. Life cycle assessment (LCA) has been used to evaluate the environmental performance of various bamboo products. This study compared the Global Warming Potential (GWP) values of bamboo products with those of the corresponding benchmark materials (e.g., steel, concrete, plastics) through a comprehensive literature review of relevant LCA studies. The results showed that bamboo products often lead to lower GWP values. In several other cases, we also observed significant variability in the comparison results due to a wide range of assumptions regarding bamboo cultivation, processing, product manufacturing, energy supply, and choices of the LCA database adopted by the reviewed studies. We analyzed the key modeling assumptions for each life cycle stage of bamboo products and established a harmonized inventory dataset to reduce the uncertainty in modeling the processed bamboo (as a raw material for subsequently manufacturing various products). Based on the harmonized dataset, we conducted a cradle-to-gate LCA and concluded that the major contributor to the overall GWP result was electricity consumption (and associated carbon intensity of energy generation) during bamboo processing. We also concluded that future research was needed to improve the transparency, consistency, and comprehensiveness of LCA studies on bamboo products.

Global scenarios of resource and emission savings from material efficiency in residential buildings and cars.

Material production accounts for a quarter of global greenhouse gas (GHG) emissions. Resource-efficiency and circular-economy strategies, both industry and demand-focused, promise emission reductions through reducing material use, but detailed assessments of their GHG reduction potential are lacking. We present a global-scale analysis of material efficiency for passenger vehicles and residential buildings. We estimate future changes in material flows and energy use due to increased yields, light design, material substitution, extended service life, and increased service efficiency, reuse, and recycling. Together, these strategies can reduce cumulative global GHG emissions until 2050 by 20-52 Gt CO2-eq (residential buildings) and 13-26 Gt CO2e-eq (passenger vehicles), depending on policy assumptions. Next to energy efficiency and low-carbon energy supply, material efficiency is the third pillar of deep decarbonization for these sectors. For residential buildings, wood construction and reduced floorspace show the highest potential. For passenger vehicles, it is ride sharing and car sharing.

A solvent-free approach to extract the lipid fraction from sewer grease for biodiesel production.

Fats, oils and greases (FOG) are the number one cause of sewer pipe blockage and have been mostly disposed of as a waste until recently. This study investigated a low cost and environmentally friendly approach to extract the lipid fraction (fatty acids and glycerides for biodiesel production) from sewer grease (SG), i.e., FOGs obtained from wastewater treatment plants (WWTPs). The lipid fraction of the sewer grease was primarily in the form of free fatty acid (FFA), at 20.7wt%. An innovative solvent-free extraction approach was developed using waste cooking oil (WCO) to overcome the challenges of emulsion, impurities and high moisture content of the sewer grease. A 95% extraction yield of sewer grease was achieved under the optimum operating condition of 3.2:1 WCO-SG ratio (wt/wt), 70°C and 240min. In addition, the reusability of the WCO was also investigated. WCO can be used two to three times for sewer grease extraction with more than 90% extraction efficiency.

Converting campus waste into renewable energy - a case study for the University of Cincinnati.

This paper evaluates the implementation of three waste-to-energy projects at the University of Cincinnati: waste cooking oil-to-biodiesel, waste paper-to-fuel pellets and food waste-to-biogas, respectively. The implementation of these waste-to-energy (WTE) projects would lead to the improvement of campus sustainability by minimizing waste management efforts and reducing GHG emissions via the displacement of fossil fuel usage. Technical and economic aspects of their implementation were assessed and the corresponding GHG reduction was estimated. Results showed that on-site implementation of these projects would: (1) divert 3682L (974 gallons) of waste cooking oil to 3712L (982 gallons) of biodiesel; (2) produce 138tonnes of fuel pellets from 133tonnes of waste paper (with the addition of 20.75tonnes of plastics) to replace121tonnes of coal; and (3) produce biogas that would be enough to replace 12,767m(3) natural gas every year from 146tonnes of food waste. The economic analysis determined that the payback periods for the three projects would be 16months for the biodiesel, 155months for the fuel pellet, and 74months for the biogas projects. The reduction of GHG emission from the implementation of the three WTE projects was determined to be 9.37 (biodiesel), 260.49 (fuel pellets), and 11.36 (biogas) tonnes of CO2-eq per year, respectively.